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Value-based data engineering
September 14, 2023
Answering predetermined questions was based on a centralized and well-articulated data model, but failed to enable data exploration, experimentation and evolution of the data-driven business strategy. These failures only get worse with time as more data needs to be integrated and the platform becomes more fragile to change. Ultimately this fails to deliver timely and competitive business results. As we’ve seen, providing known data to answer known questions can be done using many well-known data architectures, but that’s only part of the story.
The benefits of a data warehouse vs. data lake vs. data lakehouse
August 29, 2023
Adopting a data lakehouse architecture over a traditional data warehouse comes with many business benefits. In fact, these differences are often the key reason that organizations make the transition from older technologies to modern ones. Let’s explore the business case for the adoption of a data lakehouse, also known as modern data lake, and see how it can improve versatility, maintain performance, and reduce costs. To do this, we’ll compare the differences between a data warehouse and data lake then discuss the hybrid advantage of a data lakehouse.
What data engineers can learn from lean manufacturing
August 24, 2023
Starburst offers a shift – a shift left to a more lean model of delivering data for analytics bringing the compute to the data, instead of the data to the compute.
BestSecret’s data journey: Moving beyond Snowflake
August 16, 2023
Of all the seventy-plus speakers at the festival, there was one presentation that I found to be particularly interesting – and not because the speaker also happens to be our customer. That presentation was from Lutz Künneke, Director of Engineering, and Isa Inalcik, Senior Data Engineer, at BestSecret, a leading European online destination for off-price fashion based near Munich, Germany. As Künneke got to the stage, the first words out of his mouth were: “We are moving off of Snowflake.”
Operationalizing data products at scale with AI
August 14, 2023
We explore how AI and data products are coming together to improve the user experience and to accelerate the delivery of innovative business solutions. Some of these are based on conceptual discussions, and others are based on actual use cases. Early strategic vision is usually painted with some crayons (curiosity and imagination) and watercolors (experience and detail).
Harnessing Trino for performance engineering and data analytics at Salesforce
August 8, 2023
Learn how Salesforce uses Trino for data analytics and performance engineering, boosting service availability and customer experiences through efficient insights and real-time data access.
Narrow the evidence gap in patient care with faster access to real-world evidence
July 18, 2023
Clinicians often make critical patient-care decisions based on anecdotal observations and personal experiences, emphasizing the urgent need for faster access to real-world evidence to support and enhance clinical decision-making.
Generative AI and Starburst: Pioneering natural language interfaces for data exploration
July 11, 2023
Unlocking the Potential: Language Models (LLMs) offer exciting possibilities in data analytics and query processing. Join us as we explore their strengths, limitations, and our future plans at Starburst
Comment Starburst Galaxy augmente et optimise votre cloud data warehouse
June 23, 2023
Lire l’article en anglais Snowflake est le grand leader du cloud data warehouse (CDW). Snowflake a été le premier à proposer une plate-forme SQL...
Four traps to avoid when developing data products
June 14, 2023
In this article, we’ll discuss four traps that can disrupt data product development and how to avoid falling into them. These bad practices are focusing on quantity over quality, ignoring stakeholder feedback, overlooking collaboration, and putting off governance.
Data products and data mesh: how they relate, and how they are different
June 8, 2023
Despite innovations in data architecture, infrastructure, and analytics, most organizations today still struggle to realize the promised value of data. Learn how the data mesh principle of data as a product can help, as part of a data mesh initiative or as a stand-alone strategy.
What to consider when designing a data lake analytics architecture for a startup
June 6, 2023
Of all the choices a startup has to make in its early stages, deciding on the right data analytics architecture might not seem critical,...
